1. Field
The present systems, methods and apparatus relate to superconducting shielding techniques for use with integrated circuits for quantum computing.
2. Description of the Related Art
A Turing machine is a theoretical computing system, described in 1936 by Alan Turing. A Turing machine that can efficiently simulate any other Turing machine is called a Universal Turing Machine (UTM). The Church-Turing thesis states that any practical computing model has either the equivalent or a subset of the capabilities of a UTM.
An analog processor is a processor that employs fundamental properties of a physical system to find the solution to a computation problem. In contrast to a digital processor, which requires an algorithm for finding the solution followed by the execution of each step in the algorithm according to Boolean methods, analog processors do not involve Boolean methods.
A quantum computer is any physical system that harnesses one or more quantum effects to perform a computation. A quantum computer that can efficiently simulate any other quantum computer is called a Universal Quantum Computer (UQC).
In 1981 Richard P. Feynman proposed that quantum computers could be used to solve certain computational problems more efficiently than a UTM and therefore invalidate the Church-Turing thesis. See e.g., Feynman R. P., “Simulating Physics with Computers”, International Journal of Theoretical Physics, Vol. 21 (1982) pp. 467-488. For example, Feynman noted that a quantum computer could be used to simulate certain other quantum systems, allowing exponentially faster calculation of certain properties of the simulated quantum system than is possible using a UTM.
Approaches to Quantum Computation
There are several general approaches to the design and operation of quantum computers. One such approach is the “circuit model” of quantum computation. In this approach, qubits are acted upon by sequences of logical gates that are the compiled representation of an algorithm. Circuit model quantum computers have several serious barriers to practical implementation. In the circuit model, it is required that qubits remain coherent over time periods much longer than the single-gate time. This requirement arises because circuit model quantum computers require operations that are collectively called quantum error correction in order to operate. Quantum error correction cannot be performed without the circuit model quantum computer's qubits being capable of maintaining quantum coherence over time periods on the order of 1,000 times the single-gate time. Much research has been focused on developing qubits with coherence sufficient to form the basic information units of circuit model quantum computers. See e.g., Shor, P. W. “Introduction to Quantum Algorithms”, arXiv.org:quant-ph/0005003 (2001), pp. 1-27. The art is still hampered by an inability to increase the coherence of qubits to acceptable levels for designing and operating practical circuit model quantum computers.
Another approach to quantum computation, involves using the natural physical evolution of a system of coupled quantum systems as a computational system. This approach does not make critical use of quantum gates and circuits. Instead, starting from a known initial Hamiltonian, it relies upon the guided physical evolution of a system of coupled quantum systems wherein the problem to be solved has been encoded in the terms of the system's Hamiltonian, so that the final state of the system of coupled quantum systems contains information relating to the answer to the problem to be solved. This approach does not require long qubit coherence times. Examples of this type of approach include adiabatic quantum computation, cluster-state quantum computation, one-way quantum computation, quantum annealing and classical annealing, and are described, for example, in Farhi, E. et al., “Quantum Adiabatic Evolution Algorithms versus Stimulated Annealing” arXiv.org:quant-ph/0201031 (2002), pp 1-24.
Qubits
As mentioned previously, qubits can be used as fundamental units of information for a quantum computer. As with bits in UTMs, qubits can refer to at least two distinct quantities; a qubit can refer to the actual physical device in which information is stored, and it can also refer to the unit of information itself, abstracted away from its physical device.
Qubits generalize the concept of a classical digital bit. A classical information storage device can encode two discrete states, typically labeled “0” and “1”. Physically these two discrete states are represented by two different and distinguishable physical states of the classical information storage device, such as direction or magnitude of magnetic field, current, or voltage, where the quantity encoding the bit state behaves according to the laws of classical physics. A qubit also contains two discrete physical states, which can also be labeled “0” and “1”. Physically these two discrete states are represented by two different and distinguishable physical states of the quantum information storage device, such as direction or magnitude of magnetic field, current, or voltage, where the quantity encoding the bit state behaves according to the laws of quantum physics. If the physical quantity that stores these states behaves quantum mechanically, the device can additionally be placed in a superposition of 0 and 1. That is, the qubit can exist in both a “0” and “1” state at the same time, and so can perform a computation on both states simultaneously. In general, N qubits can be in a superposition of 2N states. Quantum algorithms make use of the superposition property to speed up some computations.
In standard notation, the basis states of a qubit are referred to as the |0> and |1> states. During quantum computation, the state of a qubit, in general, is a superposition of basis states so that the qubit has a nonzero probability of occupying the |0> basis state and a simultaneous nonzero probability of occupying the |1> basis state. Mathematically, a superposition of basis states means that the overall state of the qubit, which is denoted |Ψ>, has the form |Ψ>=a|0>+b|1>), where a and b are coefficients corresponding to the probabilities |a|2 and |b|2, respectively. The coefficients a and b each have real and imaginary components, which allows the phase of the qubit to be characterized. The quantum nature of a qubit is largely derived from its ability to exist in a coherent superposition of basis states and for the state of the qubit to have a phase. A qubit will retain this ability to exist as a coherent superposition of basis states when the qubit is sufficiently isolated from sources of decoherence.
To complete a computation using a qubit, the state of the qubit is measured (i.e., read out). Typically, when a measurement of the qubit is performed, the quantum nature of the qubit is temporarily lost and the superposition of basis states collapses to either the |0> basis state or the |1> basis state and thus regaining its similarity to a conventional bit. The actual state of the qubit after it has collapsed depends on the probabilities |a|2 and |b|2 immediately prior to the readout operation.
Superconducting Qubits
There are many different hardware and software approaches under consideration for use in quantum computers. One hardware approach uses integrated circuits formed of superconducting materials, such as aluminum or niobium. The technologies and processes involved in designing and fabricating superconducting integrated circuits are in some respects similar to those used for conventional integrated circuits.
Superconducting qubits are a type of superconducting device that can be included in a superconducting integrated circuit. Superconducting qubits can be separated into several categories depending on the physical property used to encode information. For example, they may be separated into charge, flux and phase devices, as discussed in, for example Makhlin et al., 2001, Reviews of Modern Physics 73, pp. 357-400. Charge devices store and manipulate information in the charge states of the device, where elementary charges consist of pairs of electrons called Cooper pairs. A Cooper pair has a charge of 2e and consists of two electrons bound together by, for example, a phonon interaction. See e.g., Nielsen and Chuang, Quantum Computation and Quantum Information, Cambridge University Press, Cambridge (2000), pp. 343-345. Flux devices store information in a variable related to the magnetic flux through some part of the device. Phase devices store information in a variable related to the difference in superconducting phase between two regions of the phase device. Recently, hybrid devices using two or more of charge, flux and phase degrees of freedom have been developed. See e.g., U.S. Pat. No. 6,838,694 and U.S. Patent Application No. 2005-0082519.
A qubit comprising a superconducting main loop serially-interconnected to a subloop which contains two Josephson junctions is said to employ a gradiometer-based flux qubit. An example of this approach is discussed in U.S. Pat. No. 6,984,846.
Quantum Processor
A computer processor may take the form of an analog processor, for instance a quantum processor such as a superconducting quantum processor. A superconducting quantum processor may include a number of qubits and associated local bias devices, for instance two or more superconducting qubits.
A superconducting quantum processor may include a number of coupling devices operable to selectively couple respective pairs of qubits. Examples of superconducting coupling devices include rf-SQUIDs and dc-SQUIDs, which couple qubits together by flux. SQUIDs include a superconducting loop interrupted by one Josephson junction (an rf-SQUID) or two Josephson junctions (a dc-SQUID). The coupling devices may be capable of both ferromagnetic and anti-ferromagnetic coupling, depending on how the coupling device is being utilized within the interconnected topology. In the case of flux coupling, ferromagnetic coupling implies that parallel fluxes are energetically favorable and anti-ferromagnetic coupling implies that anti-parallel fluxes are energetically favorable. Alternatively, charge-based coupling devices may also be used. Other coupling devices can be found, for example, in U.S. patent application Ser. No. 11/247,857 and U.S. Provisional Patent Application No. 60/886,253. Respective coupling strengths of the coupling devices may be tuned between zero and a maximum value, for example, to provide ferromagnetic or anti-ferromagnetic coupling between qubits.
Regardless of the specific hardware being implemented, managing a single qubit requires control over a number of parameters. Conventionally, this requirement necessitated outside communication (that is, communication from outside of the processor architecture) with individual qubits. However, since overall processing power increases with the number of qubits in the system, high capacity processors that exceed the abilities of conventional supercomputers must manage a large number of qubits and thus the conventional approach of employing outside control over multiple parameters on individual qubits requires a complicated system for programming qubit parameters.
Thus, the scalability of quantum processors is limited by the complexity of the qubit parameter control system and there remains a need in the art for a scalable qubit parameter control system.
Shielding and Noise
Magnetic fields produced by external sources may cause unwanted interactions with devices in the integrated circuit. Accordingly, there may be a need for a superconducting shield proximate to devices populating the integrated circuit to reduce the strength of interference such as magnetic and electrical fields. An example of this is discussed in WO 96/09654.
Superconducting shielding incorporated into an integrated circuit has been used to protect superconducting quantum interference device (SQUID) packages from DC and AC noise, such as magnetic and electrical fields, that would otherwise interfere with operation of the integrated circuit. Regions of the integrated circuit can be unshielded to allow for communication between magnetic and electrical fields external to the SQUID package. An example of this approach is discussed in U.S. Pat. No. 5,173,660.
Superconducting shielding layers may be used in single flux quantum (SFQ) or rapid single flux quantum (RSFQ) technology to separate devices from DC power lines that could otherwise undesirably bias the devices. The devices populate the integrated circuit but are separated from the DC power lines by placing a ground plane between the devices and the DC power line. Examples of this type of approach are described, for example, in Nagasawa et al., “Development of advanced Nb process for SFQ circuits” Physica C 412-414 (2004) 1429-1436 (herein referred to as Nagasawa) and Satoh et al., “Fabrication Process of Planarized Multi-Layer Nb Integrated Circuits” IEEE Transactions on Applied Superconductivity, Vol. 15, No. 2, (June 2005).
In SFQ circuits, ground planes and shielding layers are terminologies used interchangeably. A ground plane in SFQ integrated circuit is a layer of metal that appears to most signals within the circuit as an infinite ground potential. The ground plane helps to reduce noise within the integrated circuit but may be used to ensure that all components within the SFQ integrated circuits have a common potential to compare voltage signals. Nagasawa shows the use of contacts between wiring layers and a ground plane throughout SFQ circuitry.
Supercurrent flowing in superconducting wires has an associated magnetic field in the same manner as electrons flowing in normal metal wires. Magnetic fields can couple inductively to superconducting wires, inducing currents to flow. Quantum information processing with superconducting integrated circuits necessarily involves supercurrents moving in wires, and hence associated magnetic fields.
The quantum properties of quantum devices are very sensitive to noise, and stray magnetic fields in superconducting quantum devices can negatively impact the quantum information processing properties of such circuits. Superconducting ground planes have been used in the art to reduce cross-talk between control lines and devices. However, such approaches have only been used in superconducting integrated circuits for classical processing and sensor applications, which are relatively robust against in-circuit noise and operate at significantly higher temperatures as compared with superconducting quantum processing integrated circuits.
In superconducting quantum processing integrated circuits, it is desirable to substantially attenuate and control unwanted cross-talk between devices, otherwise quantum information processing at commercial scales may not be possible. The present methods, systems and apparatus provide techniques for attenuating cross-talk in superconducting quantum processing integrated circuits between quantum devices in order to support the desired quantum effects and controllably couple quantum devices in a manner that permits exchange of coherent quantum information.